Hitherto, image techniques for detecting a photographic subject reflected to the picture have been studied. In case that an image recognition device detects a subject in an image, various processes that are suitable for the subject may be applied to the image. For example, the image recognition device may make the subject more visible by converting the tones of the image in accordance with the subject, or trim the subject area from the image.
Preferably, a subject is known in advance, in order to detect it precisely. This is because when a subject is known, an image recognition device may detect this subject from an image by making use of information regarding the characteristics of the subject, such as a shape, color and texture. In fact, however, an image recognition device may detect an unknown subject. In this case, it is difficult for the image recognition device to recognize what a subject is, and to discriminate between a subject area and the other area in an image.
Meanwhile, techniques have been proposed which detect a region containing a specific shape, such as a partially depressed portion, in order to detect a subject in an image. For example, an image processing device for medical diagnosis extracts a boundary corresponding to a contour of a target organ, as a contour line. Then, this image processing device corrects the shape of the contour line, and acquires it as a contour line of the target organ. When correcting the shape of the contour line, in case of finding a concave inflection point located between two convex inflection points, the image processing device removes a portion between the convex inflection points, as a depressed portion. Moreover, for example, an organ volume measurement device designates six points on a boundary of an organ, as initial points, and extracts the boundary on the basis of these points. Then, the organ volume measurement device sets boundary existing regions on each organ cross section successively from the result of extracting the boundary, and extracts boundaries therein. When extracting the boundaries, the organ volume measurement device detects a depressed portion on the boundary of the organ, on the basis of a positional relationship of the adjacent points on the boundary.
Moreover, for example, an image analysis device extracts, from an image containing a target region, a segment of a boundary of the target region which corresponds to a depressed portion. This image analysis device sets target region outside points which are arranged along the boundary at regular intervals and at a predetermined distance away from the boundary in the normal direction thereof. Then, the image analysis device applies weights to points in a circle, the center of which is located at each target region outside point, and detects the most weighted portion as a depressed region.
Moreover, for example, a vectorization method of a figure detects a right-angled part of a recessed portion in sequential pixels on a contour, on the basis of a chain code representing an edge direction of the contour. For example, an image processing method successively tracks a boundary pixel between adjacent enveloped points in a direction from one point to the other point, and estimates a distance between the center of the boundary pixel and a line formed by connecting the adjacent points, thereby detecting a depressed portion.
Unfortunately, the conventional techniques make use of information on a subject to be detected, in order to detect a depressed portion on the contour or boundary of the subject. For example, using information regarding a contour of a subject (target organ) which has a slightly curved segment, the above-described image processing device for medical diagnosis can detect a depressed portion on the contour, on the basis of the change in the curvature of the contour. Accordingly, unless any information regarding a subject is available, it is difficult to apply the above-described techniques to detect the subject in an image. Furthermore, another above-described technique can be applied to detect a right-angled part of a recessed portion, but may be difficult to apply in order to detect a depressed portion on a contour having any given shape. Moreover, another technique has the precondition that enveloped points on a contour of a subject have been detected. Therefore, it is difficult to detect a depressed portion on a contour of a subject in an image when the subject area is unknown.
Examples of related art are discussed in Japanese Laid-open Patent Publication Nos. 08-89503, 2000-107183, 2010-224875, 01-68889, and 01-284984.